diff --git a/apps/enterprise-knowledge-retrieval/enterprise_knowledge_retrieval.ipynb b/apps/enterprise-knowledge-retrieval/enterprise_knowledge_retrieval.ipynb
index 6662407b..3626b065 100644
--- a/apps/enterprise-knowledge-retrieval/enterprise_knowledge_retrieval.ipynb
+++ b/apps/enterprise-knowledge-retrieval/enterprise_knowledge_retrieval.ipynb
@@ -1084,13 +1084,14 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "ca7e7eb1",
+   "id": "eb5848f3",
    "metadata": {},
    "outputs": [],
    "source": [
     "## Batch Embedding Logic\n",
     "\n",
     "# Simple function to take in a list of text objects and return them as a list of embeddings\n",
+    "@retry(wait=wait_random_exponential(min=1, max=40), stop=stop_after_attempt(10))\n",
     "def get_embeddings(input: List):\n",
     "    response = openai.Embedding.create(\n",
     "        input=input,\n",
@@ -1197,7 +1198,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "9e49c881",
+   "id": "e3a6fb12",
    "metadata": {},
    "outputs": [
     {
@@ -1222,7 +1223,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "2e6ff2f4",
+   "id": "83f0231c",
    "metadata": {},
    "outputs": [
     {
@@ -1248,7 +1249,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "963170f9",
+   "id": "61c204c8",
    "metadata": {},
    "outputs": [
     {
@@ -2649,7 +2650,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "c1b5fad4",
+   "id": "ba73ffab",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2953,7 +2954,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "id": "99072e4c",
+   "id": "4ee414f1",
    "metadata": {},
    "outputs": [
     {